A high closeness centrality score indicates that a vertex can reach
other vertices on relatively short paths; a high betweenness
centrality score indicates that a vertex lies on a relatively high
number of shortest paths.

All centrality scores are normalized.

But this normalization depends on the graph being connected.
Use ST_ConnectedComponents
to make sure you're calling ST_GraphAnalysis on a
single (strongly) connected component.

A few caveats.

Results will not be accurate if the graph:

contains "duplicate" edges (having the same source,
destination and weight)

is disconnected. If all closeness centrality scores are zero,
this is why.

Though Brande's algorithm is much faster than a naïve
approach, it still requires an augmented version of Dijkstra's
algorithm to be run starting from each vertex. Thus, calculation
times can be rather long for larger graphs.